{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the langchain related imports\n",
    "from typing import Any, List, Mapping, Optional\n",
    "\n",
    "from langchain.callbacks.manager import CallbackManagerForLLMRun\n",
    "from langchain.llms.base import LLM\n",
    "\n",
    "# if you need the agent from langchain\n",
    "from langchain.agents import load_tools\n",
    "from langchain.agents import initialize_agent\n",
    "from langchain.agents import AgentType\n",
    "\n",
    "# if you need the Conversation from langchain\n",
    "from langchain.chains import ConversationChain\n",
    "from langchain.memory import ConversationBufferMemory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import cv2\n",
    "import llama\n",
    "import torch\n",
    "from PIL import Image\n",
    "\n",
    "import os\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"6\"\n",
    "\n",
    "from llama.llama_adapter import  LLaMA_adapter\n",
    "from torchvision.transforms.transforms import Compose\n",
    "from PIL import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class LLaMALangChain(LLM):\n",
    "\n",
    "    generator: LLaMA_adapter\n",
    "    preprocess: Compose\n",
    "    device: str = \"cuda\"\n",
    "    temperature: float = 0.1\n",
    "    top_p: float = 0.75\n",
    "    max_seq_len: int = 512\n",
    "    max_gen_len: int = 64\n",
    "\n",
    "    @property\n",
    "    def _llm_type(self) -> str:\n",
    "        return \"LLaMA Adapter\"\n",
    "    \n",
    "    def _call(\n",
    "        self,\n",
    "        prompt: str,\n",
    "        stop: Optional[List[str]] = None,\n",
    "        run_manager: Optional[CallbackManagerForLLMRun] = None,\n",
    "    ) -> str:\n",
    "        # since the langchain currently does not support image input, we add image path inside the prompt\n",
    "        image_path = prompt[:prompt.find(\"<ImgPathEnd>\")]\n",
    "        img = Image.fromarray(cv2.imread(image_path))\n",
    "        img = preprocess(img).unsqueeze(0).to(device)\n",
    "\n",
    "        prompt = prompt[prompt.find(\"<ImgPathEnd>\")+len(\"<ImgPathEnd>\"):]\n",
    "        full_result = self.generator.generate(img, [prompt], max_gen_len=self.max_gen_len, temperature=self.temperature, top_p=self.top_p)[0]\n",
    "        if \"Response\" in full_result:\n",
    "            pure_response = full_result[full_result.rfind(\"Response:\")+9:]\n",
    "        else:\n",
    "            pure_response = full_result\n",
    "        # to avoid it automatically adding a self-proposed question\n",
    "        if \"### Input:\" in pure_response:\n",
    "            print(f\"### Input: found in response {pure_response}, removing it\")\n",
    "            pure_response = pure_response[:pure_response.find(\"### Input:\")]\n",
    "            print(f\"New response: {pure_response}\")\n",
    "        return pure_response\n",
    "\n",
    "\n",
    "    @property\n",
    "    def _identifying_params(self) -> Mapping[str, Any]:\n",
    "        \"\"\"Get the identifying parameters.\"\"\"\n",
    "        return {\n",
    "            \"temperature\": self.temperature,\n",
    "            \"top_p\": self.top_p,\n",
    "            \"max_seq_len\": self.max_seq_len,\n",
    "        }\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading LLaMA-Adapter from ckpts/7fa55208379faf2dd862565284101b0e4a2a72114d6490a95e432cf9d9b6c813_BIAS-7B.pth\n"
     ]
    }
   ],
   "source": [
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
    "llama_dir = \"/data1/llma\"\n",
    "model, preprocess = llama.load(\"BIAS-7B\", llama_dir, device, max_seq_len=2048)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "temperature = 0.1\n",
    "top_p = 0.75\n",
    "max_gen_len = 256\n",
    "max_seq_len = 2048\n",
    "llm = LLaMALangChain(generator=model, preprocess=preprocess, \n",
    "                    temperature=temperature, top_p=top_p, max_seq_len=max_seq_len, \n",
    "                    max_gen_len=max_gen_len, device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.prompts.prompt import PromptTemplate\n",
    "from langchain.schema import HumanMessage, AIMessage\n",
    "from langchain.memory import ChatMessageHistory\n",
    "\n",
    "\n",
    "conversation_template = \"\"\"The following is a conversation between a human and an AI. Write a response that completes the request.\n",
    "\n",
    "Current conversation:\n",
    "{history}\n",
    "### Input: {input}\n",
    "### Response:\"\"\"\n",
    "\n",
    "def conversation_fromat_prompt(input, history=None):\n",
    "    conversation_template = \"\"\"The following is a conversation between a human and an AI. Write a response that completes the request.\n",
    "\n",
    "    Current conversation:\n",
    "    {history}\n",
    "    ### Input: {input}\n",
    "    ### Response:\"\"\"\n",
    "\n",
    "    if history is not None:\n",
    "        conversation_prompt = conversation_template.format_map({'input': input, \"history\": history})\n",
    "    else:\n",
    "        conversation_prompt = conversation_template.format_map({'input': input, \"history\": \"\"})\n",
    "\n",
    "    return conversation_prompt\n",
    "\n",
    "def get_history_string(history):\n",
    "    history_str = \"\"\n",
    "    for message in history.messages:\n",
    "        if isinstance(message, AIMessage):\n",
    "            history_str += \"### Response: \" + message.content + \"\\n\"\n",
    "        else:\n",
    "            history_str += \"### Input: \" + message.content + \"\\n\\n\"\n",
    "\n",
    "def conversation_user(user_message):\n",
    "    history.add_user_message(user_message)\n",
    "    history_str = None\n",
    "    if len(history.messages) >= 2:\n",
    "        history_str = get_history_string(history)\n",
    "    prompt = conversation_fromat_prompt(user_message, history=history_str)\n",
    "    prompt = img_path + \"<ImgPathEnd>\" + prompt\n",
    "    response = llm(prompt)\n",
    "    history.add_ai_message(response)\n",
    "    history_str = get_history_string(history)\n",
    "\n",
    "    return response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fe6649e6880>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "history = ChatMessageHistory()\n",
    "img_path = \"/data1/llama_adapter_project/LLaMA-Adapter-v2-Demo-release/examples/bayern_logo.png\"\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "img = plt.imread(img_path)\n",
    "plt.axis('off')\n",
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The logo in the image is the FC Bayern Munich logo.'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_message = \"What is that Logo in the image.\"\n",
    "conversation_user(user_message)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Bayern Munich belongs to the German Bundesliga'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_message = \"To which liga belongs this team\"\n",
    "conversation_user(user_message)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The most famous player of Bayern Munich is Franck Ribery.'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_message = \"Give me one of the most famous player of that team\"\n",
    "conversation_user(user_message)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Yes, Bayern Munich has won many times champion.'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_message = \"Did this team has won many times champion?\"\n",
    "conversation_user(user_message)"
   ]
  }
 ],
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